Bibliografias temáticas / Split algorithm

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Literatura científica selecionada sobre o tema "Split algorithm"

Autor: Grafiati
Publicado: 15 de fevereiro de 2025
Última modificação: 7 de julho de 2025

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Artigos de revistas sobre o assunto "Split algorithm"

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Liang, Liang. "A Fusion Multiobjective Empire Split Algorithm." Journal of Control Science and Engineering 2020 (December 14, 2020): 1–14. http://dx.doi.org/10.1155/2020/8882086.

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In the last two decades, swarm intelligence optimization algorithms have been widely studied and applied to multiobjective optimization problems. In multiobjective optimization, reproduction operations and the balance of convergence and diversity are two crucial issues. Imperialist competitive algorithm (ICA) and sine cosine algorithm (SCA) are two potential algorithms for handling single-objective optimization problems, but the research of them in multiobjective optimization is scarce. In this paper, a fusion multiobjective empire split algorithm (FMOESA) is proposed. First, an initialization operation based on opposition-based learning strategy is hired to generate a good initial population. A new reproduction of offspring is introduced, which combines ICA and SCA. Besides, a novel power evaluation mechanism is proposed to identify individual performance, which takes into account both convergence and diversity of population. Experimental studies on several benchmark problems show that FMOESA is competitive compared with the state-of-the-art algorithms. Given both good performance and nice properties, the proposed algorithm could be an alternative tool when dealing with multiobjective optimization problems.
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Ortiz Díaz, Agustín Alejandro, Isvani Inocencio Frías Blanco, Laura María Palomino Mariño, and Fabiano Baldo. "An Online Tree-Based Approach for Mining Non-Stationary High-Speed Data Streams." Revista de Informática Teórica e Aplicada 27, no. 1 (2020): 36–47. http://dx.doi.org/10.22456/2175-2745.90822.

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This paper presents a new learning algorithm for inducing decision trees from data streams. In these domains, large amounts of data are constantly arriving over time, possibly at high speed. The proposed algorithm uses a top-down induction method for building trees, splitting leaf nodes recursively, until none of them can be expanded. The new algorithm combines two split methods in the tree induction. The first method is able to guarantee, with statistical significance, that each split chosen would be the same as that chosen using infinite examples. By doing so, it aims at ensuring that the tree induced online is close to the optimal model. However, this split method often needs too many examples to make a decision about the best split, which delays the accuracy improvement of the online predictive learning model. Therefore, the second method is used to split nodes more quickly, speeding up the tree growth. The second split method is based on the observation that larger trees are able to store more information about the training examples and to represent more complex concepts. The first split method is also used to correct splits previously suggested by the second one, when it has sufficient evidence. Finally, an additional procedure rebuilds the tree model according to the suggestions made with an adequate level of statistical significance. The proposed algorithm is empirically compared with several well-known induction algorithms for learning decision trees from data streams. In the tests it is possible to observe that the proposed algorithm is more competitive in terms of accuracy and model size using various synthetic and real world datasets.
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Pinker, Rachel T., Donglian Sun, Meng-Pai Hung, Chuan Li, and Jeffrey B. Basara. "Evaluation of Satellite Estimates of Land Surface Temperature from GOES over the United States." Journal of Applied Meteorology and Climatology 48, no. 1 (2009): 167–80. http://dx.doi.org/10.1175/2008jamc1781.1.

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Abstract A comprehensive evaluation of split-window and triple-window algorithms to estimate land surface temperature (LST) from Geostationary Operational Environmental Satellites (GOES) that were previously described by Sun and Pinker is presented. The evaluation of the split-window algorithm is done against ground observations and against independently developed algorithms. The triple-window algorithm is evaluated only for nighttime against ground observations and against the Sun and Pinker split-window (SP-SW) algorithm. The ground observations used are from the Atmospheric Radiation Measurement Program (ARM) Central Facility, Southern Great Plains site (April 1997–March 1998); from five Surface Radiation Budget Network (SURFRAD) stations (1996–2000); and from the Oklahoma Mesonet. The independent algorithms used for comparison include the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data and Information Service operational method and the following split-window algorithms: that of Price, that of Prata and Platt, two versions of that of Ulivieri, that of Vidal, two versions of that of Sobrino, that of Coll and others, the generalized split-window algorithm as described by Becker and Li and by Wan and Dozier, and the Becker and Li algorithm with water vapor correction. The evaluation against the ARM and SURFRAD observations indicates that the LST retrievals from the SP-SW algorithm are in closer agreement with the ground observations than are the other algorithms tested. When evaluated against observations from the Oklahoma Mesonet, the triple-window algorithm is found to perform better than the split-window algorithm during nighttime.
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Delsarte, P., and Y. Genin. "The split Levinson algorithm." IEEE Transactions on Acoustics, Speech, and Signal Processing 34, no. 3 (1986): 470–78. http://dx.doi.org/10.1109/tassp.1986.1164830.

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Hidayat, Trifenaus Prabu, and Andre Sugioko. "Performance Analyzes of Bee Colony Split-Plot Algorithm." International Journal of Information and Education Technology 5, no. 7 (2015): 549–52. http://dx.doi.org/10.7763/ijiet.2015.v5.566.

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Jambunathan, Suriya Prakash. "A Machine Learning-Based Approach for Antenna Design Using Class_Reg Algorithm Optimized Using Genetic Algorithm." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (2021): 1682–86. http://dx.doi.org/10.22214/ijraset.2021.39097.

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Abstract: Microstrip patch antennas are predominantly in use in mobile communication and healthcare. Their performances are even improved, using Split-Ring Resonator cells. But finding the ideal dimensions of the microstrip patch antenna and calculating the correct number and size of the split ring resonator cells consume a lot of time when we use Electromagnetic Simulation software to design first and then simulate. Using the pre-calculated results of certain sets of microstrip patch antennas with split ring resonators, a machine learning model can be trained and hence be used to predict the antenna metrics when the dimensions are specified. When the machine learning algorithms are combined with feature-optimization algorithms such as the Genetic Algorithm, the efficiency and performance can be improved further. Keywords: Machine Learning, Micro-strip Patch Antenna, Genetic algorithm, Split Ring Resonator.
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Cui, Ying Hua, Yu Ping Zhao, Hui Yang Wang, and Jin He Zhou. "Pre-Split Anti-Collision Binary Tree Algorithm." Applied Mechanics and Materials 220-223 (November 2012): 2403–6. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2403.

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In RFID system, reducing the frequency of collisions is very important for fast tag identification. In this paper, we proposed a pre-split anti-collision algorithm based on binary tree algorithm. The proposed scheme pre-splits the tags into different groups before the reader detects the first tag. Simulation results indicate that the modified algorithm can achieve much better performance than the conventional one.
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Huang, Zheng, Yanting Zhang, Lin Wang, Jingyu Xu, and Yunlong Zheng. "Research on multi-objective parameter optimization of split flow dual flash thermodynamic cycle." Journal of Physics: Conference Series 2728, no. 1 (2024): 012008. http://dx.doi.org/10.1088/1742-6596/2728/1/012008.

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Abstract In addition to considering the intermediate pressure variables, the split flow double flash thermodynamic cycle also needs to consider the operating conditions and split flow coefficient of the cycle. Traditional algorithms require too much computation and have a longer response time. Faced with sudden operating conditions or changes in production conditions, it is difficult to quickly re-optimize the intermediate parameters of the split flow double flash thermal cycle and carry out corresponding system control. This article uses intelligent optimization algorithms instead of global search methods to optimize multi-objective parameters in a split flow double flash thermodynamic cycle. By summarizing and analyzing the characteristics of algorithms such as SIO, EA, and ANN, it is believed that the GWO algorithm in the SIO class is the most suitable for multi-objective parameter optimization of the split flow double flash thermal cycle. It is combined with the SA optimization algorithm to propose the SA-GWO algorithm with faster optimization speed and higher optimization accuracy, taking the initial position of the wolf pack as the optimization objective. Combined with the cycle thermodynamic model, a multi-objective parameter optimization model for the split flow double flash thermal cycle is established.
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Ching, P. C., and K. F. Wan. "Generalised split structure adaptive algorithm." Electronics Letters 31, no. 24 (1995): 2084–85. http://dx.doi.org/10.1049/el:19951435.

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Jin, C., L. J. Lu, and J. N. Min. "A two-stage construction heuristic approach for vehicle routing problem with split deliveries and pickups: Case studies and performance comparison." Advances in Production Engineering & Management 17, no. 1 (2022): 121–33. http://dx.doi.org/10.14743/apem2022.1.425.

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The vehicle routing problem with split deliveries and pickups is a hot research topic in recent years, where a customer can be served multiple times with split deliveries and pickups. The objective is to minimize the travel distance, use the fewest number of vehicles and increase the load rate, which will further reduce the carbon emissions that damage the environment. In this paper, we use a two-stage construction heuristic approach to solve this problem. First, partitioning algorithms based on the multi-restart-iterative sweep algorithm are adopted to partition the customer domain into sub-domains according to the vehicle capacity, and to determine the split points and the corresponding values. Second, a modified Clarke-Wright savings algorithm is used to check the possibility of each point in each route based on the load of each point and the vehicle load limitation. The three case studies with 12 instances per each from the reconstructed Solomon benchmark datasets were conducted to evaluate the effectiveness and feasibility of the proposed approaches-Unsplit, Both-Split and Enhanced-Both-Split. The comparison among these approaches reveals that the splits reduce the total travel cost and vehicles used, and increase the average loading rate considerably, especially when customers have larger demand values. Our computation results proves that the vehicle routing problem with split deliveries and pickups is highly beneficial for transportation and logistics enterprises.
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Teses / dissertações sobre o assunto "Split algorithm"

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Liu, Rongrong. "A Novel Attack Method Against Split Manufactured Circuits." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1573812230926837.

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Shi, Haijian. "Best-first Decision Tree Learning." The University of Waikato, 2007. http://hdl.handle.net/10289/2317.

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In best-first top-down induction of decision trees, the best split is added in each step (e.g. the split that maximally reduces the Gini index). This is in contrast to the standard depth-first traversal of a tree. The resulting tree will be the same, just how it is built is different. The objective of this project is to investigate whether it is possible to determine an appropriate tree size on practical datasets by combining best-first decision tree growth with cross-validation-based selection of the number of expansions that are performed. Pre-pruning, post-pruning, CART-pruning can be performed this way to compare.
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Lian, Tea Sormbroen. "Computing Almost Split Sequences : An algorithm for computing almost split sequences of finitely generated modules over a finite dimensional algebra." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for matematiske fag, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-19355.

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An artin algebra $l$ over a commutative, local, artinian ring $R$ was fixed, and with this foundation some topics from representation theory were discussed. A series of functors of module categories were defined, and almost split sequences were introduced with some basic results. An isomorphism $omega_{delta,X} : D delta^* rightarrow delta_*(DTr(X))$ of $Gamma$-modules for an artin $R$-algebra $Gamma$ was constructed. The isomorphism $omega_{delta,X}$ was applied to a special case, yielding a deterministic algorithm for computing almost split sequences in the case that $R$ is a field.
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Lakshman, Prabhashankar. "Parallel implementation of the split and merge algorithm on the hypercube machine." Ohio : Ohio University, 1989. http://www.ohiolink.edu/etd/view.cgi?ohiou1182440993.

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Brochier, Felipe Osmar Berwanger. "Otimização de um condicionador de ar do tipo split com vazão variável de refrigerante." Universidade do Vale do Rio dos Sinos, 2014. http://www.repositorio.jesuita.org.br/handle/UNISINOS/4619.

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Submitted by Fabricia Fialho Reginato (fabriciar) on 2015-07-23T01:11:46Z No. of bitstreams: 1 FelipeBrochier.pdf: 2248315 bytes, checksum: 51a12fbb2e530bf08f1847557932b381 (MD5)<br>Made available in DSpace on 2015-07-23T01:11:46Z (GMT). No. of bitstreams: 1 FelipeBrochier.pdf: 2248315 bytes, checksum: 51a12fbb2e530bf08f1847557932b381 (MD5) Previous issue date: 2014-02<br>Nenhuma<br>Este trabalho tem como objetivo otimizar o custo operacional dependente dos parâmetros de vazão de ar do condensador, número de aletas e de circuitos do condensador, frequência do compressor e parâmetros do dispositivo de expansão de um sistema de um condicionador de ar do tipo split hiwall unitário com vazão variável de refrigerante (VRV). Para a otimização foram consideradas as freqüências de ocorrência de quatro condições de temperatura do ambiente externo na cidade de Porto Alegre. O condicionador de ar abordado neste trabalho troca calor utilizando um ciclo de compressão de vapor de simples estágio, tendo como fluido de trabalho o refrigerante R-410A. O sistema completo, composto de um compressor, um condensador, um evaporador e tubo capilar, foi modelado analiticamente utilizando o software EES (Engineering Equation Solver) e ajustado de acordo com testes realizados em calorímetro. Para a otimização, um algoritmo genético foi programado no próprio EES. Após a otimização do custo operacional em função dos parâmetros físicos de projeto, o COP aumentou em até 12 % na condição de ar externo a 35 °C. A otimização em função dos parâmetros de controle mostrou aumento ainda mais significativo do COP do sistema. Também é feita uma comparação entre os valores de COP de um sistema de vazão constante de ar e refrigerante e um sistema com vazão variável de ar e refrigerante.<br>This work aims to optimize the operational cost of an air conditioning system with variable refrigerant flow (VRF). The cost is dependent of the following parameters: condenser air flow, number of condenser fins and circuits, compressor frequency and the expansion device. The optimization considered the frequencies of occurrence of four distinct ambient temperatures in the city of Porto Alegre. The air conditioner presented in this work exchange heat using a single stage vapor compression cycle, with the refrigerant R-410A as the working fluid. The complete system comprises a compressor, a condenser, an evaporator and a capillary tube and was analytically modeled using the EES (Engineering Equation Solver) software. The parameters were fitted according to results obtained in a calorimeter and for optimization, a genetic algorithm was programmed using the same software. After the optimization of the operational cost as a function of the project parameters, the COP was raised up to 12% in external ambient air at 35 °C. The optimization of the operational cost as a function of the control parameters showed even a more significant system COP raise. A comparison between the COP of a constant air and refrigerant flow system and a variable air and refrigerant flow system was also performed.
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Shwayder, Kobey. "The best binary split algorithm a deterministic method for dividing vowel inventories into contrastive distinctive features /." Waltham, Mass. : Brandeis University, 2009. http://dcoll.brandeis.edu/handle/10192/23254.

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Chen, Yuan. "A Fast, Passive and Accurate Model Generation Algorithm for RLCG Transmission Lines with Skin Effects." University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1116250638.

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Rao, Michaël. "Décompositions de graphes et algorithmes efficaces." Metz, 2006. http://docnum.univ-lorraine.fr/public/UPV-M/Theses/2006/Rao.Michael.SMZ0607.pdf.

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Ce mémoire traite de la décomposition modulaire ainsi que différentes de ses généralisations. Dans un premier temps, on explique comment se servir de décompositions pour résoudre efficacement certains problèmes sur les graphes. En particulier, en utilisant la décomposition modulaire, on obtient des algorithmes linéaires pour les problèmes " ensemble stable ", " clique ", " nombre chromatique " et " partition en cliques " sur les graphes sans P_5 et gem induit. On étudie également comment la décomposition en coupes peut servir pour calculer le nombre chromatique, et on exhibe une nouvelle classe de problèmes de partitionnements pour lesquels on peut obtenir des algorithmes polynomiaux sur les graphes de largeur de clique bornée. Dans un second temps, on s'intéresse à généraliser la décomposition modulaire. On étudiera une nouvelle décomposition appelée décomposition bi-joint. On donne notamment différentes caractérisations des graphes complètement décomposables par cette décomposition, et un algorithme linéaire pour la calculer. On donne également des généralisations paramétrées de la décomposition modulaire, qui s'avèrent relativement proches de la largeur de clique<br>This thesis deals with the modular decomposition and several of its generalizations. In a first time we show how graph decompositions can be used to solve efficiently some problems on graphs. We show how the modular decomposition can be used to obtain linear algorithms for " independent set ", " clique ", " chromatic number " and " partition into cliques " on (P_5,gem)-free graphs. We also show how the split decomposition can be used to compute the chromatic number, and we give a new class of vertex partitioning problems which can be solved in polynomial time on graphs of bounded clique width. In a second time, we are interested to generalize the modular decomposition. We study a new decomposition called the bi-join decomposition. We give in particular several characterizations of completely decomposable graphs, and a linear time decomposition algorithm. We introduce some parametrized generalization of the modular decomposition, and we show that theses generalizations are relatively close to the clique width
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Frigo, Nadia. "Composite likelihood inference in state space models." Doctoral thesis, Università degli studi di Padova, 2010. http://hdl.handle.net/11577/3426576.

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In general state space models, where the computational effort required in the evaluation of the full likelihood function is infeasible, we analyze the problem of static parameter estimation based on composite likelihood functions, in particular pairwise and split data likelihood functions. We discuss consistency and efficiency properties of these estimators (related to the characteristics of the model) and the bias in stationary models where the invariant distribution is unknown. We focus on numerical methods to compute estimates of the parameter describing a general state space model. We develop an on line Expectation- Maximization algorithm in order to obtain the maximum pairwise likelihood estimate in a general state space framework. We illustrate this method for a linear gaussian model and we extend it to make inference also in jump Markov linear systems. In this framework, some sampling procedures need to be developed to estimate the parameters of the model. In particular, we present an algorithm to sample from the latent discrete state Markov chain given the pairs of observations.<br>Nell’ambito di modelli state space, per i quali ricavare la funzione di verosimiglianza completa non è computazionalmente possibile, si è analizzato il problema della stima di parametri statici mediante funzioni di verosimiglianza composita, in particolare funzioni di verosimiglianza a coppie e a blocchi. L’interesse si è concentrato sullo studio delle proprietà di consistenza e di efficienza di tali stimatori (in relazione alle caratteristiche del processo stazionario sottostante il modello) nonchè su problemi di distorsione in modelli stazionari per i quali la distribuzione invariante non è nota. Sono stati presi in esame metodi numerici per il calcolo delle stime dei parametri che descrivono un modello state space generale. Si è sviluppato un algoritmo Expectation- Maximization sequenziale per ottenere stime di massima verosimiglianza a coppie nel contesto di modelli state space generali. Tale metodo è illustrato per modelli lineari gaussiani e viene esteso per l’inferenza in sistemi lineari markoviani con salti. In questo contesto, è stato necessario sviluppare adeguate procedure di campionamento. In particolare, viene presentato un algoritmo per campionare dalla catena markoviana a stati discreti date le coppie di osservazioni.
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Perdigão, Martino Diego. "Stratégies d'optimisation pour le problème intégré de transport et de gestion de stock." Electronic Thesis or Diss., Université Clermont Auvergne (2021-...), 2024. http://www.theses.fr/2024UCFA0139.

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Les problèmes de gestion de stock et de routage de véhicule sont des défis logistiques qui peuvent influencer de manière significative l'efficacité et l'efficience des opérations de la chaîne logistique et doivent être bien coordonnées et alignées. Les gérer conjointement est encore plus difficile lorsqu'on prend en compte le nombre de clients à servir et la durée de l'horizon de temps. Dans la littérature, ce problème est connu sous le nom de Inventory Routing Problem (IRP) et vise à trouver une solution de coût minimum qui traite les problèmes de stock et de transport simultanément. L'IRP a été introduit pour la première fois en 1983 par Bell et al. et a attiré jusqu'à présent l'attention de la communauté RO, qui a introduit de nombreuses extensions et fourni des données pour favoriser la recherche et les comparaisons justes.En recherche, certaines lacunes existent, et l'IRP n'est pas une exception. La plupart des travaux existants supposent que la flotte de véhicules utilisée pour les livraisons est homogène et que les coûts associés au stockage des produits et aux besoins des clients sont constants et égaux tout au long de l'horizon, ce qui ne correspond pas à un scénario réel. De plus, la livraison d'un seul produit par période est souvent considérée, ce qui n'est pas rentable.Cette thèse aborde l'IRP et introduit une nouvelle variante qui est plus proche d'un scénario logistique réel en incorporant une flotte de véhicules hétérogène, des demandes de clients et des coûts d'inventaire dépendants des périodes. De plus, on considère que les clients préfèrent recevoir des produits en lots plutôt qu'à l'unité. Pour cela, un nouveau jeu d'instances est introduit pour prendre en compte ces nouvelles caractéristiques. Cette variante, appelée Heterogeneous Inventory Routing Problem with Batch Size (HIRP-BS), est étudiée en utilisant trois approches.La première est un modèle mathématique qui étend une formulation de flux existante pour incorporer les caractéristiques du HIRP-BS. De nouvelles variables et contraintes sont alors nécessaires pour cela. Il n'est pas surprenant que la formulation ne soit pas capable de résoudre les instances à grande échelle et que même celles à échelle moyenne soient difficiles à résoudre dans un temps raisonnable.La deuxième méthode proposée est un algorithme itératif qui décompose l'IRP en autant de sous-problèmes que de périodes. Le but est de résoudre les sous-problèmes dans l'ordre chronologique et à chaque itération (à l'exception de la première, correspondant à la première période), d'utiliser la solution obtenue précédemment comme point de départ pour la période actuelle. Les changements sont limités par un paramètre d'entrée pour accélérer la convergence. L'idée générale est que pour une période donnée, les itérations suivantes devraient nécessiter de modifications intelligentes des solutions précédentes et que le nombre de changements devrait diminuer à mesure qu'on approche de la fin de l'horizon.La troisième méthode est une métaheuristique basée sur un algorithme emph{split} qui décompose une séquence multi-période de clients, appelée tour géant, en routes qui sont attribués à une période et à un type de véhicule. L'algorithme débute par le calcul des quantités estimées et des périodes pour le réapprovisionnement, en supposant les opérations de livraison au dernier moment. Il permet la définition d'un tour géant qui est évalué à l'aide d'un algorithme split responsable pour définir des solutions réalisables pour le problème. Ensuite, un mécanisme de recherche locale dédié au problème de routage utilise les opérateurs classiques basés sur les routes. A la fin, une phase de post-optimisation est considérée, améliorant la qualité de la solution en termes de stock et transport, basée sur une notion de distance. Les résultats sont prometteurs en termes de convergence et peuvent fournir des bornes supérieures valides dans un délai raisonnable, même pour les instances à grande échelle<br>Inventory management and vehicle routing problems are logistic challenges that can significantly influence the efficiency and effectiveness of supply chain operations and should be well-coordinated and aligned. Handling both jointly is even more challenging when considering the number of customers to be served and the length of the time horizon. In the literature, this problem is known as the Inventory Routing Problem (IRP) and aims to find a minimum-cost solution that addresses both inventory and transportation problems simultaneously. The IRP was first introduced in 1983 by Bell et al. and have received a lot of attention from the OR community so far, which has introduced numerous extensions and provided datasets to favor research and fair comparisons.In research, some gaps exist, and the IRP is not an exception. Most works in the literature so far assume that the fleet of vehicles used for the deliveries is homogeneous and that the costs associated with product storage and customer needs are constant and equal over the entire time horizon, which is not in accordance with a real scenario. Also, a single-item delivery per period is often considered by the formulation, which is clearly not cost-effective.This thesis addresses the IRP and introduces a new variant that is closer to a real logistic scenario by incorporating a heterogeneous vehicle fleet, customer demands, and inventory holding costs that are period-dependent. Additionally, it considers that customers may prefer receiving products in batches rather than in single units. For that, a new set of instances is introduced to handle these new features. This novel variant, named the Heterogeneous Inventory Routing Problem with Batch Size (HIRP-BS), is studied using three approaches. The first one is a mathematical formulation that extends a flow formulation initially designed to handle the HIRP-BS characteristics. New variables and constraints are then required to consider the new incorporated features. Not surprisingly, the formulation is not capable of handling large-scale instances and even the medium-scale ones are hard to solve in a timely manner. The second method is an iterative algorithm which decomposes the original IRP into as many sub-problems as periods of time are considered. The idea is to solve the sub-problems in chronological order such that at each iteration (except for the first, which corresponds to the first period), it uses the solution obtained in the previous as a starting point for the current one. The changes are limited by an input parameter to accelerate convergence. The overall idea is that for a given period, the following iterations should require smart modification of the previous solutions of the partial problem already solved and that the number of changes should decrease once it approaches the end of the time horizon.The third method is a split-based metaheuristic that decomposes a multi-period sequence of customers, called a giant tour, into routes that are assigned to a period and a vehicle type. The contribution leads to a new multi-period Split algorithm. It starts with the computation of the estimated quantities and periods for the replenishment, assuming the delivery operations at the latest possible moment. It allows the definition of a giant tour that is evaluated through a Split algorithm responsible for defining feasible solutions for the problem. Then, a local search mechanism dedicated to the routing problem takes advantage of classical route-based operators. Lastly, a post-optimization phase is considered, and slightly improve solution quality in terms of inventory and routing aspects based on a solution distance notion. Results are promising in terms of convergence and can provide valid upper bounds in a reasonable time even for the large-scale instances proposed
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Livros sobre o assunto "Split algorithm"

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Institute for Computer Applications in Science and Engineering. and United States. National Aeronautics and Space Administration., eds. Parallel directionally split solver based on reformulation of pipelined Thomas algorithm. Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1998.

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2

Anderson, W. Kyle. Three-dimensional multigrid algorithms for the flux-split Euler equations. National Aeronautics and Space Administration, Scientific and Technical Information Division, 1989.

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1952-, Thomas James L., Whitfield David L, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., eds. Three-dimensional multigrid algorithms for the flux-split Euler equations. National Aeronautics and Space Administration, Scientific and Technical Information Division, 1989.

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Anderson, W. Kyle. Three-dimensional multigrid algorithms for the flux-split Euler equations. National Aeronautics and Space Administration, Scientific and Technical Information Division, 1989.

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5

Anderson, W. Kyle. Three-dimensional multigrid algorithms for the flux-split Euler equations. Langley Research Center, 1988.

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6

United States. National Aeronautics and Space Administration., ed. Implicit multigrid algorithms for the three-dimensional flux split Euler equations. National Aeronautics and Space Administration, 1986.

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B, Grossman, and United States. National Aeronautics and Space Administration., eds. Calculation of hypersonic shock structure using flux-splut algorithms. Interdiciplinmary Center for Applied Mathematics, Virginia Polytechnic Institute and State University, 1991.

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8

United States. National Aeronautics and Space Administration. and Mississippi State University. Dept. of Aerophysics and Aerospace Engineering., eds. Adaptive grid embedding for the two-dimensional flux-split Euler equations. Mississippi State University, Dept. of Aerospace Engineering, 1990.

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Implicit multigrid algorithms for the three-dimensional flux split Euler equations. National Aeronautics and Space Administration, 1986.

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10

Das, Vinu V., and Passent M. El-Kafrawy. Signal Processing and Information Technology: Second International Joint Conference, SPIT 2012, Dubai, UAE, September 20-21, 2012, Revised Selected Papers. Springer, 2014.

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Capítulos de livros sobre o assunto "Split algorithm"

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Ounali, Chedi, Fahmi Ben Rejab, and Kaouther Nouira Ferchichi. "Incremental Algorithm Based on Split Technique." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16660-1_55.

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Ghosh, Esha, Sudeshna Kolay, Mrinal Kumar, et al. "Faster Parameterized Algorithms for Deletion to Split Graphs." In Algorithm Theory – SWAT 2012. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31155-0_10.

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Manikandan, V., and S. Monikandan. "Algorithm for Reconstruction Number of Split Graphs." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2066-8_5.

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Zhang, Lijing, Xuanhui He, and Yulan Ren. "Research on the Improved Algorithm of Node Split." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25349-2_134.

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Setzer, Simon. "Split Bregman Algorithm, Douglas-Rachford Splitting and Frame Shrinkage." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02256-2_39.

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Ochelska-Mierzejewska, Joanna. "Ant Colony Optimization Algorithm for Split Delivery Vehicle Routing Problem." In Advanced Information Networking and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44041-1_67.

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Chau, Kwok-wing. "A Split-Step PSO Algorithm in Predicting Construction Litigation Outcome." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-36668-3_163.

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Odashima, Shigeyuki, Miwa Ueki, and Naoyuki Sawasaki. "A Split-Merge DP-means Algorithm to Avoid Local Minima." In Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46227-1_5.

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Drescher, Matthew, Samuel Fiorini, and Tony Huynh. "A Simple $$(2+\epsilon )$$-Approximation Algorithm for Split Vertex Deletion." In Trends in Mathematics. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-83823-2_48.

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Zhang, Han, Qing Li, and Xin Yao. "Knowledge-Guided Optimization for Complex Vehicle Routing with 3D Loading Constraints." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70055-2_9.

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AbstractThe split delivery vehicle routing problem with three-dimensional loading constraints (3L-SDVRP) intertwines complex routing and packing challenges. The current study addresses 3L-SDVRP using intelligent optimization algorithms, which iteratively evolve towards optimal solutions. A pivotal aspect of these algorithms is search operators that determine the search direction and the search step size. Effective operators significantly improve algorithmic performance. Traditional operators like swap, shift, and 2-opt fall short in complex scenarios like 3L-SDVRP, mainly due to their limited capacity to leverage domain knowledge. Additionally, the search step size is crucial: smaller steps enhance fine-grained search (exploitation), while larger steps facilitate exploring new areas (exploration). However, optimally balancing these step sizes remains an unresolved issue in 3L-SDVRP. To address this, we introduce an adaptive knowledge-guided insertion (AKI) operator. This innovative operator uses node distribution characteristics for adaptive node insertion, enhancing search abilities through domain knowledge integration and larger step sizes. Integrating AKI with the local search framework, we develop an adaptive knowledge-guided search (AKS) algorithm, which effectively balances exploitation and exploration by combining traditional neighbourhood operators for detailed searches with the AKI operator for broader exploration. Our experiments demonstrate that the AKS algorithm significantly outperforms the state-of-the-art method in solving various 3L-SDVRP instances.
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Trabalhos de conferências sobre o assunto "Split algorithm"

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Maurice, Nathan, Julien Sopena, and Lionel Lacassagne. "A New Efficient Split & Merge Algorithm for Embedded Systems." In 2024 IEEE International Conference on Image Processing (ICIP). IEEE, 2024. http://dx.doi.org/10.1109/icip51287.2024.10648097.

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Ghosh, Anjan, and Paparao Palacharla. "Efficient optical preprocessing using split-step algorithms." In OSA Annual Meeting. Optica Publishing Group, 1989. http://dx.doi.org/10.1364/oam.1989.tudd2.

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A new and efficient split-step polynomial preconditioning algorithm is discussed. In this algorithm, basic polynomial preconditioning iterations are repeated several times, each time with an improved matrix. With minor modifications this algorithm can be used for matrix inversion and condition number estimation. The split-step algorithms consist of two nested iterative loops involving matrix multiplications and thus are attractive for parallel optical processors. The details of realization of splitstep algorithms on three different optical matrix multiplier architectures are outlined. The condition number after m outer loop iterations is given by1/{1−[1−1/c(a)] pm }, where p is the number of inner loop iterations and C(A) is the initial condition number.1 This strategy reduces the condition number approximately at the rate O(p −m ), much faster compared to other preconditioning algorithms. The results of numerical experiments on the split-step algorithm applied to a case study of an optimum phased array antenna design problem show that this new preconditioning algorithm is a viable tool for improving the performance of analog optical processors. Preliminary analyses of the split-step algorithm demonstrate its robustness with regard to the spatial errors and noise present in most optical processors. Using these split-step algorithms an interconnected optical processor capable of computing solutions with a specified accuracy can be designed.
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Wu, C. H., and A. E. Yagle. "The gradient adaptive split lattice algorithm." In [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 1992. http://dx.doi.org/10.1109/icassp.1992.226447.

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Boeva, Veselka, Milena Angelova, and Elena Tsiporkova. "A Split-Merge Evolutionary Clustering Algorithm." In 11th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007573103370346.

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Sun, Jian, Hongyu Jia, Bo Hu, et al. "Speeding up Very Fast Decision Tree with Low Computational Cost." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/177.

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Very Fast Decision Tree (VFDT) is one of the most widely used online decision tree induction algorithms, and it provides high classification accuracy with theoretical guarantees. In VFDT, the split-attempt operation is essential for leaf-split. It is computation-intensive since it computes the heuristic measure of all attributes of a leaf. To reduce split-attempts, VFDT tries to split at constant intervals (for example, every 200 examples). However, this mechanism introduces split-delay for split can only happen at fixed intervals, which slows down the growth of VFDT and finally lowers accuracy. To address this problem, we first devise an online incremental algorithm that computes the heuristic measure of an attribute with a much lower computational cost. Then a subset of attributes is carefully selected to find a potential split timing using this algorithm. A split-attempt will be carried out once the timing is verified. By the whole process, computational cost and split-delay are lowered significantly. Comprehensive experiments are conducted using multiple synthetic and real datasets. Compared with state-of-the-art algorithms, our method reduces split-attempts by about 5 to 10 times on average with much lower split-delay, which makes our algorithm run faster and more accurate.
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Combettes, Patrick L., and Jean-Christophe Pesquet. "Split convex minimization algorithm for signal recovery." In ICASSP 2009 - 2009 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2009. http://dx.doi.org/10.1109/icassp.2009.4959676.

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Ling, Hangkun. "Emulating Expert Systems and the Location-Identity Split." In 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018). Atlantis Press, 2018. http://dx.doi.org/10.2991/cmsa-18.2018.19.

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Zhang, Zheyu, Tianping Zhang, and Jian Li. "Unbiased Gradient Boosting Decision Tree with Unbiased Feature Importance." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/515.

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Gradient Boosting Decision Tree (GBDT) has achieved remarkable success in a wide variety of applications. The split finding algorithm, which determines the tree construction process, is one of the most crucial components of GBDT. However, the split finding algorithm has long been criticized for its bias towards features with a large number of potential splits. This bias introduces severe interpretability and overfitting issues in GBDT. To this end, we provide a fine-grained analysis of bias in GBDT and demonstrate that the bias originates from 1) the systematic bias in the gain estimation of each split and 2) the bias in the split finding algorithm resulting from the use of the same data to evaluate the split improvement and determine the best split. Based on the analysis, we propose unbiased gain, a new unbiased measurement of gain importance using out-of-bag samples. Moreover, we incorporate the unbiased property into the split finding algorithm and develop UnbiasedGBM to solve the overfitting issue of GBDT. We assess the performance of UnbiasedGBM and unbiased gain in a large-scale empirical study comprising 60 datasets and show that: 1) UnbiasedGBM exhibits better performance than popular GBDT implementations such as LightGBM, XGBoost, and Catboost on average on the 60 datasets and 2) unbiased gain achieves better average performance in feature selection than popular feature importance methods.
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Faruquzzaman, A. B. M., Nafize Rabbani Paiker, Jahidul Arafat, Ziaul Karim, and M. Ameer Ali. "Object segmentation based on split and merge algorithm." In TENCON 2008 - 2008 IEEE Region 10 Conference (TENCON). IEEE, 2008. http://dx.doi.org/10.1109/tencon.2008.4766802.

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Wu, Xindong. "TS: a test-split algorithm for inductive learning." In Optical Engineering and Photonics in Aerospace Sensing, edited by Firooz A. Sadjadi. SPIE, 1993. http://dx.doi.org/10.1117/12.150598.

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Relatórios de organizações sobre o assunto "Split algorithm"

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Warren, Russell, Stanley Osher, and Richard Vanderbeek. Multiple Aerosol Unmixing by the Split Bregman Algorithm. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada555738.

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Barrios, Amalia E., and Kenneth H. Craig. Rough Surface Models Implemented Within the Split-Step Parabolic Equation Algorithm. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada280843.

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Ostashev, Vladimir, Michael Muhlestein, and D. Wilson. Extra-wide-angle parabolic equations in motionless and moving media. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42043.

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Wide-angle parabolic equations (WAPEs) play an important role in physics. They are derived by an expansion of a square-root pseudo-differential operator in one-way wave equations, and then solved by finite-difference techniques. In the present paper, a different approach is suggested. The starting point is an extra-wide-angle parabolic equation (EWAPE) valid for small variations of the refractive index of a medium. This equation is written in an integral form, solved by a perturbation technique, and transformed to the spectral domain. The resulting split-step spectral algorithm for the EWAPE accounts for the propagation angles up to 90° with respect to the nominal direction. This EWAPE is also generalized to large variations in the refractive index. It is shown that WAPEs known in the literature are particular cases of the two EWAPEs. This provides an alternative derivation of the WAPEs, enables a better understanding of the underlying physics and ranges of their applicability, and opens an opportunity for innovative algorithms. Sound propagation in both motionless and moving media is considered. The split-step spectral algorithm is particularly useful in the latter case since complicated partial derivatives of the sound pressure and medium velocity reduce to wave vectors (essentially, propagation angles) in the spectral domain.
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Zhao, George, Grang Mei, Bulent Ayhan, Chiman Kwan, and Venu Varma. DTRS57-04-C-10053 Wave Electromagnetic Acoustic Transducer for ILI of Pipelines. Pipeline Research Council International, Inc. (PRCI), 2005. http://dx.doi.org/10.55274/r0012049.

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In this project, Intelligent Automation, Incorporated (IAI) and Oak Ridge National Lab (ORNL) propose a novel and integrated approach to inspect the mechanical dents and metal loss in pipelines. It combines the state-of-the-art SH wave Electromagnetic Acoustic Transducer (EMAT) technique, through detailed numerical modeling, data collection instrumentation, and advanced signal processing and pattern classifications, to detect and characterize mechanical defects in the underground pipeline transportation infrastructures. The technique has four components: (1) thorough guided wave modal analysis, (2) recently developed three-dimensional (3-D) Boundary Element Method (BEM) for best operational condition selection and defect feature extraction, (3) ultrasonic Shear Horizontal (SH) waves EMAT sensor design and data collection, and (4) advanced signal processing algorithm like a nonlinear split-spectrum filter, Principal Component Analysis (PCA) and Discriminant Analysis (DA) for signal-to-noise-ratio enhancement, crack signature extraction, and pattern classification. This technology not only can effectively address the problems with the existing methods, i.e., to detect the mechanical dents and metal loss in the pipelines consistently and reliably but also it is able to determine the defect shape and size to a certain extent.
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Szymczak, William G. Viscous Split Algorithms for the Time Dependent Incompressible Navier Stokes Equations. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada211592.

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